How Omics Data Can Be Used in Nephrology

被引:20
|
作者
Rhee, Eugene P. [1 ,2 ]
机构
[1] Massachusetts Gen Hosp, Nephrol Div, Boston, MA 02114 USA
[2] Massachusetts Gen Hosp, Endocrinol Div, Boston, MA 02114 USA
基金
美国国家卫生研究院;
关键词
DIABETIC KIDNEY-DISEASE; TRIMETHYLAMINE N-OXIDE; STAGE RENAL-DISEASE; MASS-SPECTROMETRY; HEMODIALYSIS-PATIENTS; METABOLOMIC ANALYSIS; URINARY PROTEOMICS; AFRICAN-AMERICANS; PLASMA; GENE;
D O I
10.1053/j.ajkd.2017.12.008
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Advances in technology and computing now permit the high-throughput analysis of multiple domains of biological information, including the genome, transcriptome, proteome, and metabolome. These omics approaches, particularly comprehensive analysis of the genome, have catalyzed major discoveries in science and medicine, including in nephrology. However, they also generate large complex data sets that can be difficult to synthesize from a clinical perspective. This article seeks to provide an overview that makes omics technologies relevant to the practicing nephrologist, framing these tools as an extension of how we approach patient care in the clinic. More specifically, omics technologies reinforce the impact that genetic mutations can have on a range of kidney disorders, expand the catalogue of uremic molecules that accumulate in blood with kidney failure, enhance our ability to scrutinize urine beyond urinalysis for insight on renal pathology, and enable more extensive characterization of kidney tissue when a biopsy is performed. Although assay methodologies vary widely, all omics technologies share a common conceptual framework that embraces unbiased discovery at the molecular level. Ultimately, the application of these technologies seeks to elucidate a more mechanistic and individualized approach to the diagnosis and treatment of human disease.
引用
收藏
页码:129 / 135
页数:7
相关论文
共 50 条
  • [21] HOW IT CAN BE USED ... (FUNCTION OF ANALYST)
    POTAMIANOU, A
    REVUE FRANCAISE DE PSYCHANALYSE, 1978, 42 (01): : 111 - 122
  • [22] Whose data can we trust: How meta-predictions can be used to uncover credible respondents in survey data
    Radas, Sonja
    Prelec, Drazen
    PLOS ONE, 2019, 14 (12):
  • [23] Causality at the dawn of the 'omics' era in medicine and in nephrology
    Zoccali, Carmine
    Brancaccio, Diego
    Nathan, Marco J.
    NEPHROLOGY DIALYSIS TRANSPLANTATION, 2016, 31 (09) : 1381 - 1385
  • [24] How can we make nephrology more appealing to junior doctors?
    Ortega Suarez, F.
    NEFROLOGIA, 2011, 31 (02): : 129 - 130
  • [25] How flash mobs can be used for data collection in healthcare? A scoping review protocol
    Gamst-Jensen, Hejdi
    Brix, Lone Dragnes
    Collet, Marie Oxenboll
    Nielsen, Anne Hojager
    ACTA ANAESTHESIOLOGICA SCANDINAVICA, 2024, 68 (06) : 857 - 860
  • [26] How can never event data be used to reflect or improve hospital safety performance*?*
    Olivarius-McAllister, J.
    Pandit, M.
    Sykes, A.
    Pandit, J. J.
    ANAESTHESIA, 2021, 76 (12) : 1616 - 1624
  • [27] How data from the bone and joint decade can be used for campaigning by the social leagues
    Woolf, A. D.
    ANNALS OF THE RHEUMATIC DISEASES, 2006, 65 : 11 - 12
  • [28] How can data from economic studies be used. The example of ankylosing spondylitis
    Boonen, A.
    ANNALS OF THE RHEUMATIC DISEASES, 2006, 65 : 11 - 11
  • [29] Big Data Challenges, Techniques, Technologies, and Applications and How Deep Learning can be Used
    Chen, C. L. Philip
    2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2016, : 3 - 3
  • [30] How spatial omics approaches can be used to map the biological impacts of stress in psychiatric disorders: a perspective, overview and technical guide
    Curry, Amber R.
    Ooi, Lezanne
    Matosin, Natalie
    STRESS-THE INTERNATIONAL JOURNAL ON THE BIOLOGY OF STRESS, 2024, 27 (01):